Jensen Huang

or written by a book that, you know, from somebody I don't know, to knowledge generated by AI computers that are assimilating all of this and resynthesizing things.

To me, I don't think there's a whole lot of difference.

We still have to fact check it.

We still have to make sure that it's, you know, based on fundamental first principles.

And we still have to do all of that, just like we do today.

I think that if you reflect back 10 years from now, you would say the same thing, that we would have never believed that.

In a different direction.

Right.

But if you go forward nine years from now and then ask yourself what's going to happen 10 years from now, I think it will be quite gradual.

Yeah, I think, let's see.

Let me start with the more mundane, and I'll work backwards, work forward.

So one of the predictions from Jeff Hinton, who started the whole deep learning phenomenon, deep learning technology trend,

And incredible, incredible researcher, professor at University of Toronto.

He invented, discovered, or invented the idea of backpropagation, which allows the neural network to learn.

And as you know, for the audience,

Software historically was humans applying first principles in our thinking to describe an algorithm that is then codified just like a recipe that's codified in software.

It looks just like a recipe.

How to cook something looks exactly the same, just in a slightly different language.

We call it Python or C or C++ or whatever it is.

In the case of deep learning, this invention of artificial intelligence, we put a structure of a whole bunch of neural networks and a whole bunch of math units.